Integración por la acción: Trama Lana

The previous section has described:

 The level of information flow within the MI domain (both types and complexity)

 The diverse information structures and the importance of structure compatibility and consistency.

 The rates of information processing, the levels at which it is processed.

 The potential risk and impact of inconsistent MI definitions.

 The different rates of change across an organization.

This section will describe why the heterogeneous nature of system and information structure rates of change is a significant challenge to maintaining MI system functionality and

interoperability.

Figure 3-18 shows a simple set of 4 systems (systems A,B,C1 and C2) with simple information flows (Da,Db1 and Db2). This model is to transition to a future state where system B is split into two systems and systems C1 and C2 are combined into a single system. It can be seen that all of the data flows, including their content and structure, are required to change. It is usual, however, for there to be an interim state as the systems do not change at the same rate, as can be seen in the figure, and this creates a complex interim state where the outputs from Systems Bf1 and Bf2 need to provide a consistent flow of information (i.e. Db1 and Db2) to Systems C1 and C2 from the new inputs Daf1 and af2.

Figure 3-18 - The complexity of heterogeneous system change

When this model is considered in the context of the previous sections i.e. the levels of information sharing, systems and timescale disparity the full complexity and challenge of maintaining consistent processes, systems and information flow is apparent.

3.6 Summary

The key findings of the work to understand MI systems interoperability issues were:

 Manufacturing Intelligence Systems and information flows are complex and numerous and operate across all levels of the organisation

 These MI information flows are required to provide and support different info structures, even at a local level.

 The definitions of/ used in MI system can be inconsistent across an enterprise undermining the ability to share information

 Definition inconsistency is compounded the more the MI information is processed hence enterprise system are at the greatest risk.

 The defined MI system and information flow and the process level/ metric level definitions can be aligned to the ISA 95 system timescales model

 The same model of MI definition inconsistency used across an organisation can be used to describe inconsistency through time.

 The risk of MI system and information definition inconsistency over time is

proportional to the rate of change of systems in Information structure, hence MI is a key area of hazard.

 A generic lifecycle can be used to describe systems and information structure change process. These lifecycles can be used to represent the non uniform rates of change.

 Heterogeneous system and information structure changes combined with the number of information types and systems and hence opportunities for inconsistency make MI systems information sharing over time a significant challenge.

The impact on an enterprise of these issues can be summarized as:

• An inability to create, update or maintain complex, integrated legacy systems resulting in potentially catastrophic business continuity risks. This also results in the failure to adopt systems improvements which can put the enterprise at a competitive disadvantage.

• A motivation to avoid systems interoperation or integration leading to ‘islands of information’ and making manufacturing decisions on incomplete information.

• Significant effort required on manual data collection and collation which due to its manual nature cannot meet the speed, accuracy or reliability requirements for MI decision making.

• An inability to consistently specify new MI systems, leading to system incompatibility

be misinterpreting each other and not functioning as intended without the users being aware.

• The reliance on standards to manage these issues means the systems can only develop as fast as the standards, and the wider the standards are used the more difficult consensus on updates is to achieve and so change becomes slower, as such a widely deployed standard would be unable to support the rate of change at the manufacturing operational level.

• Limited understanding or ability to express the requirements of systems as

individuals and as a network leading to Enterprise system requirements over-riding manufacturing or operational level requirements due to them being generally recognized as more business critical without understanding either the impact of the alternative options.

• Lack of robust methods of ensuring system consistency results in the requirement for massive regression testing to mitigate the business continuity risk. This level of testing constrains ability to adopt change, as well as having a significant cost and resource impact i.e. if this testing is not practicable, the change cannot be addopted.

The impact summarised above results in an inability to create or maintain automated MI systems across a large organization. These systems are, and will be increasingly, required to optimize manufacturing enterprises and make good manufacturing decisions in a timely manner; this inability will therefore limit the effectiveness and competitiveness of these organizations.

4 A novel approach to manufacturing systems interoperability in dynamic change environments

4.1 Introduction

In this chapter the requirements for the solution concept are explored and the solution concept described. Based on this novel core concept ontology based solution, a set of research questions are defined. These research questions provide the framework for the research and testing activities.